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EXECUTIVE SUMMARY

The research that follows concerns the various
impacts of community notification and registration laws (Meganís Law) in New
Jersey. Although this report includes a variety of interesting findings and many
ideas that will be explored upon post grant period, this research was embarked
upon, in general, to investigate: 1) the effect of Meganís Law on the overall
rate of sexual offending over time; 2) its specific deterrence effect on
re-offending, including the level of general and sexual offense recidivism, the
nature of sexual re-offenses, and time to first re-arrest for sexual and
non-sexual re-offenses (i.e., community tenure); and 3) the costs of
implementation and annual expenditures of Meganís Law. These three primary foci
were investigated using three different methodologies and samples. Phase One was
a 21-year (10 years prior and 10 years after implementation, and the year of
implementation) trend study of sex offenses in each of New Jerseyís counties and
of the state as a whole. In Phase Two, data on 550 sexual offenders released
during the years 1990 to 2000 were collected, and outcomes of interest were
analyzed. Finally, Phase Three collected implementation and ongoing costs of
administering Meganís Law. The following points highlight the major findings of
the three phases of the study.

∑New Jersey, as a whole, has experienced a
consistent downward trend of sexual offense rates with a significant change in
the trend in 1994.

∑In all but two counties, sexual offense rates were
highest prior to 1994 and were lowest after 1995.

∑County trends exhibit substantial variation and do
not reflect the statewide trend, suggesting that the statewide change point in
1994 is an artifact of aggregation.

∑In the offender release sample, there is a
consistent downward trend in re-arrests, reconvictions and re-incarcerations
over time similar to that observed in the trend study, except in 1995 when all
measures spiked to a high for that period. This resulted in

∑significant differences between cohorts (i.e.,
those released prior to and after Meganís Law was implemented).

∑Re-arrests for violent crime (whether sexual or
not) also declined steadily over the same period, resulting in a significant
difference between cohorts (i.e., those released prior to and after Meganís Law
was implemented).

∑Meganís Law has no effect on community tenure
(i.e., time to first re-arrest).

∑Meganís Law showed no demonstrable effect in
reducing sexual re-offenses.

∑Meganís Law has no effect on the type of sexual
re-offense or first time sexual offense (still largely child
molestation/incest).

∑Meganís Law has no effect on reducing the number of
victims involved in sexual offenses.

∑Sentences received prior to Meganís Law were nearly
twice as long as those received after Meganís Law was passed, but time served
was approximately the same.

∑Significantly fewer sexual offenders have been
paroled after the implementation of Meganís Law than before (this is largely due
to changes in sentencing).

∑Costs associated with the initial implementation as
well as ongoing expenditures continue to grow over time. Start up costs totaled
$555,565 and current costs (in 2007) totaled approximately 3.9 million dollars
for the responding counties.

∑Given the lack of demonstrated effect of Meganís
Law on sexual offenses, the growing costs may not be justifiable.

INTRODUCTION

On July 29, 1994,
Jesse Timmendequas, a sex offender who had been
released after serving a maximum sentence in a New Jersey correctional facility,
raped and murdered seven-year-old Megan
Kanka
in Hamilton, New Jersey. The intense community reaction that followed extended
well beyond the state. One expression of community outrage was the enactment of
laws to notify the public of the presence of sex offenders living and working in
their community. The premise was, and still is, that with this knowledge,
citizens will take protective measures against these nearby sex offenders. As
Beck, Clingermayer, Ramsey and Travis (2004) note, ďExactly what action is
expected is not clear, but it is hoped that, armed with this critical
information, citizens will work on their own or in concert with government to
make their neighborhoods saferĒ (p. 142).

During the following decade, all 50 states and
the District of Columbia enacted some version of such community registration and
notification laws, collectively referred to as ďMeganís LawsĒ (Presser &
Gunnison, 1999; Zevitz & Farkas, 2000). Although a few states, such as
Washington, had enacted community notification laws prior to 1994, the
federalization of community notification laws in 1996 created strong incentives
for other states to follow suit (Presser & Gunnison, 1999).

The legislation known as Meganís Law, includes
both registration and notification. Sex offenders must register their addresses
with local police jurisdictions within a specified time of release from prison.
By way of the registration process, the public is then notified of the
offenderís presence in the neighborhood. The goal of notification is to inform
both the public and past victims so that they can protect themselves
accordingly. As with other states, registration and notification are separate
steps in New Jersey, but are often referred to as one process. In New Jersey,
offenders are placed into one of three tiers, representing a hierarchy of
potential risk of an offenderís re-offense. A risk assessment instrument is used
to predict the offenderís likelihood of re-offense, which ultimately determines
placement into the tier. Tier one represents the lowest risk and requires only
notification of law enforcement officials and the victims. Offenders are
considered low risk and eligible for a tier one placement if they received a low
risk assessment score and are on probation / parole, receiving therapy, employed
and free of alcohol and drugs. A tier two classification represents a moderate
risk of a re-offense. It requires notification of organizations, educational
institutions, day care centers and summer camps. The factors for placement into
a tier two category include a moderate to high risk assessment score, failure to
comply with supervision, lack of employment, abuse of drugs or alcohol, denial
of offenses, lack of remorse, history of loitering or stalking children and
making threats (Brooks, 1996; Matson & Lieb, 1997; Witt & Barone, 2004). Tier
three offenders are those who are predicted to present the greatest risk to
re-offend. This category has generated the most legal resistance because it
calls for the broadest level of notification. The entire community is notified
through posters and pamphlets. The factors necessary for the placement into a
tier three category are a high probability of re-offending evidenced by a
particularly heinous instant offense or a high-risk assessment score, repetitive
and compulsive behavior, sexual preference for children, failure or refusal of
treatment, denial of the offense and lack of remorse (Brooks, 1996; Rudin, 1996;
Witt & Barone, 2004).

Despite their existence for over a decade, little
work has been done to examine the effectiveness of these laws on sexual offense
rates. A few researchers, such as Beck and colleagues (2004), have conducted
surveys to determine what protection methods community members use when given
information regarding the presence of sex offenders. Beck and colleagues (2004)
approach their research from the viewpoint that community notification laws were
enacted more to change the behaviors of potential victims than those of
potential sexual recidivists. In this study, Beck and colleagues (2004)
differentiated between two types of protective measures: (1) ďself-protective
measures,Ē or behavioral measures initiated by the potential victims themselves;
and (2) ďaltruistic protective measures,Ē or behavioral measures initiated by
family members to protect other household members (e.g., their children) (Beck &
Travis, 2002). These studies found that community notification did, in fact,
increase altruistic behaviors by community members to protect members of their
households, although the findings are inconsistent with regard to whether
self-protective behaviors increased after community notification. Because of
these results, Beck and colleagues (2004) posit that it is not the enactment of
community notification laws themselves that influences protective behaviors, but
the community membersí perceived risk of victimization (also measured in these
surveys) that mediates these behaviors. This mediating factor presents problems
for identifying the true effect of these laws on sexual recidivism rates.

A few studies have also surveyed sex offenders to
determine the impact that community notification laws have had upon them.
Tewksbury (2005) found that social stigmatization, loss of relationships,
employment and housing, and both verbal and physical assaults were experienced
by a significant minority of registered sex offenders (see also Tewksbury &
Lees, 2006). Zevitz and Farkas (2000) also found that a majority of sex
offenders reported negative consequences, such as exclusion from residences,
threats and harassment, emotional harm to their family members, social exclusion
by neighbors, and loss of employment. Furthermore, according to many tier three
offenders interviewed, these laws would not deter them from committing future
sex offenses (Zevitz and Farkas, 2000). In fact, Presser and Gunnison (1999)
suggest that notification laws may be counterproductive in that public scrutiny
causes additional stress to offenders who are transitioning back into the
community. The fear of exposure may cause offenders to avoid treatment, and in
the case of pedophiles, may encourage offenders to seek out children as a result
of adult isolation. If these assumptions are true, the risk of recidivism may be
increased (Presser & Gunnison, 1999), or at least such factors would work
against any protective measures taken, thus lessening or eliminating any
positive effect of the law.

None of the aforementioned research, however,
addresses the critical question of whether community notification and
registration laws actually reduce sex offense rates (primary offenses or
re-offenses) in the communities in which the laws are applied, or what patterns
of sexual offense rates appear. Despite Meganís Laws being in effect in all 50
states, only one study was found that examines pre and post-Meganís Law sex
offense rates. That study, conducted in the state of Washington, compared sexual
recidivism rates between two groups of sexual offenders: one released three
years prior to the implementation of community notification laws in that state,
and one released three years after the implementation. The pre and post- target
groups were those most likely to be affected by the law (i.e., those who would
qualify for tier three classification). To account for population differences,
offenders in both groups were matched on the number of sex convictions and the
type of victim (i.e., adult or child) (Schramm & Milloy, 1995). Their analysis
of potential group differences revealed that at the end of 54 months (four-and
one- half years ďat riskĒ), there was no statistically significant difference in
the arrest rates for sex offenses between the two groups (19 percent versus 22
percent). However, the study did find that notification had an effect on the
time of the next arrest for any type of offense.

Offenders subject to notification were arrested
for new crimes much more quickly than were offenders not subject to
notification. (Schramm & Milloy, 1995).

These results suggest that Meganís Laws may not
be effective in reducing recidivism rates. One can make a case, in fact, that
Meganís Law, at least as implemented in Washington, had no effect on the rate of
sex offense recidivism, although it may result in more rapid detection of new
sex offenses (see discussion in Pawson, 2002).

This lack of outcome studies means that Meganís
Laws constitute an untested mandate in the domain of empirical research. Despite
widespread community support for these laws, there is virtually no evidence to
support their effectiveness in reducing either new first-time sex offenses
(through protective measures or general deterrence) or sex re-offenses (through
protective measures and specific deterrence).

The study described below investigates various
impacts of community notification and registration laws (Meganís Law) in New
Jersey. The primary areas of study are: 1) the effect of Meganís Law on the
overall rate of sexual offending over time; 2) its specific deterrence effect on
re-offending, including the level of general and sexual offense recidivism, the
nature of sexual re-offenses, and time to first re-arrest for sexual and
non-sexual re-offenses (i.e. community tenure); and 3) the costs of implementing
and maintaining Meganís Law. These three primary foci were investigated using
three different methodologies and samples.

Phase One was a 21-year (10 years prior and 10
years after implementation, and the year of implementation) trend study of sex
offenses in each of New Jerseyís counties and the state as a whole. In Phase
Two, data on 550 sexual offenders released during the years 1990 to 2000 were
collected, and outcomes of interest were analyzed. Finally, Phase Three
collected implementation and ongoing costs of administering Meganís Law.

PHASE ONE: THE TREND STUDY

This study attempts to remedy one aspect of the
gap between the lack of research and the legislation, by examining the trend of
sexual offense rates between and within the 21 counties of New Jersey from 1985
through 2005. The study was conducted in New Jersey, the state in which Megan
Kanka was a victim and the subsequent origin of Meganís Law. Phase One is a
trend study, which will provide information on whether statistical differences
exist in sex offending arrests before and after the implementation of Meganís
Law.

The trend analysis focuses on the pattern of
sexual offense rates in New Jersey over a 21-year timeframe while comparing them
to drug offense rates and non-sexually based offending rates. The data represent
crime rates for the state as a whole and for each of the 21 counties for the ten
years prior to the legislation and the ten years after the enactment of the
legislation and includes the first full year in which Meganís Law was
implemented (i.e., 1995).

Methods

The purpose of this study is to determine whether
Meganís Law had an effect on the rate of sexual offending in New Jersey. Several
different analyses were conducted to answer this primary question. First, a
trend analysis of New Jersey sex offense rates pre and post-Meganís Law
implementation provides both a visual and statistical test of effectiveness.
Second, aggregation sometimes masks important differences at a lower level.
Therefore, the same trend analyses were conducted on each of the 21 counties in
New Jersey. Third, historical effects broader than that solely for sex offenses
may be responsible for observed changes (i.e., an observed effect of Meganís Law
may be spurious). Two comparative analyses at the state level were conducted to
contrast changes in rates of sex offenses to other offenses (i.e., drug and
other non-sex/non-drug) over the same period of time. These additional analyses
were made in an effort to place sex crimes in the context of overall crime and a
specific crime (drugs) that has been subjected to several types of legislation.

Sample and Data Collection

This study is based upon a simple pre-post
research design to determine whether any significant changes in the rates of
sexually based offenses reported by law enforcement agencies occurred after the
implementation of New Jerseyís Meganís Law in late 1994. Rates for sexually
based offenses, non-sexually based offenses, and drug offenses were collected
for the years 1985 through 2005 in order to construct a comparative trend
analysis. Data for the three types of crime were collected for all 21 counties
of New Jersey, using Uniform Crime Report (UCR) numbers for years 1985 through
2005.

Prevalence rates for the three offense categories
were established using population estimates from the Department of Laborís
Bureau of Labor Statistics. The Department of Laborís population estimates for
New Jersey were cross-referenced with the Sourcebook of Criminal Justice
Statistics, a yearly federal government publication. Because no significant
differences in population estimates were found between these two sources, UCR
numbers were used for trend analyses conducted in this study. In order to
compare state and county trends in sexually based offenses, non-sexually based
offenses, and drug abuse violations, UCR aggregate numbers and prevalence rates
for years 1985-2005 were entered into an Excel spreadsheet and SPSS.

Definitions and
Measures

Uniform Crime Report statistics are based upon
number of arrests, and as such, use of the term ďoffensesĒ in this study refers
to number of reported arrests. Three crime categories were used for trend
analysis comparisons: 1) sexually-based offenses, 2) drug offenses, and 3) other
offenses (non-sex/non-drug). Analyzing the single set of sex offense rates for
the 21-year time span provides an initial test of rate change. Across the US,
crime rates in general have been dropping since the late 1990ís. The inclusion
of all New Jersey non-sex/non-drug crime rate trends presents a visual contrast:
(1) to confirm/disconfirm the national trends, and (2) to contextualize the sex
offense rate trend within the general trends. Other offenses allow a control for
New Jersey specific historical factors that might influence rates across crime
categories, such as increased or decreased enforcement or prosecutorial budgets,
the number of police or probation officers, or aggressiveness of prosecutorsí
and the State Attorney Generalís offices.

Drug offenses, like sex offenses, have been the
target of law enforcement policies. Although drug offense rates may change over
time based upon what drugs are most common, drug arrests rates are also
particularly vulnerable to changes in federal and local policies and law
enforcement efforts. Furthermore, although the contrast between drug and sex
crimes may not be immediately obvious, the inclusion of drug offense rate trends
provides an opportunity: (1) to demonstrate the variations in rates over time,
and (2) to evaluate whether these variations have similar patterns to those of
sex offense rates.[1]

These crime categories were based on the stateís Uniform Crime
Report (UCR), a yearly statistical report based upon crimes reported to law
enforcement agencies throughout the State of New Jersey. Definitions of certain
sexually-based crimes, such as rape, were clarified via phone interviews with
the New Jersey State Police in December 2006. In addition, legal definitions of
specific crimes (e.g. endangering the welfare of a child) were verified by
reviewing Title 2C of the New Jersey Code of Criminal Justice in LexisNexis
Academic. Because ďRapeĒ is designated as a separate category by the UCR, the
UCR categories ďRapeĒ and ďSex OffensesĒ were combined under the category
ďSexually-Based OffensesĒ for the purposes of this study. The category
ďNon-Sexually Based OffensesĒ is comprised of all UCR categories except ďRapeĒ,
ďSex OffensesĒ and ďDrug OffensesĒ. Furthermore, ďDrug OffensesĒ included
various types of drug crimes, such as the manufacturing and distribution of
controlled substances, possession with the intent to sell and distribution of a
controlled substance within a school zone.

Analytic Strategy

In
studies of this type, typically a simple pre-post test of rates is conducted to
determine whether an intervention is successful. Given that these data are
points in time, namely crime rates by year, time based strategies are commonly
used, including time-series/ARIMA models and regression discontinuity designs
that allow for temporal autocorrelation. These analyses are constructed based
upon a known change point. Although it is known that Meganís Law was passed in
late 1994, it is not known when the agencies charged with implementing the law
were fully prepared to do so. Further, Meganís Law may not have been uniformly
implemented across the state at a standardized point. The earliest change point
that might be attributed to the legislation, therefore, is between 1994 and
1995. Given delayed implementation, the true effect of the legislation may occur
during a subsequent year. For this study, a method is required that will allow
for the detection of such delayed effects.

Several authors have considered the problem of change-points (see Pettitt, 1979
for a brief review). Some make assumptions regarding the nature of the pre and
post-change sample distributions. Most assume that the change-point is known.
Pettitt (1979) offers a solution to the crime trend problem by suggesting a
method of determining the most probable point of change and using a
non-parametric procedure to test for significance. The logic of Pettittís
argument is summarized below.

Assume a sequence of random variables; X1, X2, ... , XT and a change-point at ,
where Xt for t = 1, ... , have a distribution function of F1(x) and Xt for t =
+1, ... , T have a distribution function of F2(x) and F1(x) F2(x). Since the
change-point is unknown, T-1 two sample comparisons are necessary. In the
complete sample of T,

Ut,T
= 2Wt Ė t(T +1)

where Wt is the sum of the
ranks of all observations from 1 to t. This produces a U statistic for each
point in the time series comparing the mean of the series prior to t with the
mean of the series after t. A version of the Mann-Whitney U statistic, used to
test that the two samples, X1, ... , Xt and Xt +1 , ... , XT , come from the
same population, is applied to the maximum U value:

KT = max |Ut,T|1< t < T

The approximation of
significance probabilities that is associated with KT is:

P ≡2 exp
(-6k2/ (T 2 + T 3))

where the approximation
holds accurate to two decimal places for p< .5 (Pettitt, 1979).

This analysis employs
this technique used to determine significant differences when the change point
is unknown. This technique was selected specifically because we did not want to
make any assumptions regarding the implementation phase. In most cases, where a
law requires changes to procedure, the effect is likely to be delayed by some
unknown period.

Data from the 21 New
Jersey counties were entered separately, the New Jersey total was aggregated
from the countiesí summary numbers and the resulting rates were adjusted for
year-to-year population changes at the state level. For each county and for the
state as a whole, the yearly rates were rank ordered and a Mann-Whitney U test
was performed to test for a change in trend. Thus, for the state and for each
county, every year is tested as a potential change point.

Results

The
results are organized into two major sections. The first section presents the
trend analysis for both the state and for the individual counties. The second
section contrasts the sex offense trend rates to trends in other offenses (i.e.,
drug and other non-sex/non-drug) over the same period of time.

County and Statewide
Sex Offense Rates

Figure 1
displays the rates of sex offenses for New Jersey as a whole from 1985 to 2005.
The rates varied from 51 offenses in 1986 to a low of 29 offenses per 100,000
population in 2005. In general, there is a consistent downward trend.

Individual counties varied substantially both between counties and within
counties over time. Table 1 presents summary statistics of
each county and the state as a whole. Counties varied in population size from
under 100,000 population in the smallest counties of Cape May, Salem, and
Warren, to over three quarters of a million residents in the largest counties of
Bergen and Essex. The population size of the county is not consistently related
to the rate of sex offenses. For example, one of the largest counties, Essex
County (Newark), has a relatively high rate of offenses (68), whereas the
largest county, Bergen, has a relatively low rate (32). In contrast, the highest
rate of offenses is in one of the smaller population counties, Cumberland. In
the smallest counties, Cape May has a rate of 72 offenses per 100,000, whereas
Warren has a rate of 36.

In 19 of the 21 counties, the year
with the highest rate of sex offenses occurred before 1994; Passaic and Sussex
Counties were the exceptions. In 19 of the 21 counties, the year with the lowest
rate of sex offenses occurred after 1995; Morris and Passaic Counties were the
exceptions in this case.

The rank trend tests
(Mann-Whitney U tests) revealed that (1) six counties had no statistically
significant change point (Bergen, Hunterdon, Mercer, Morris, Passaic and
Sussex), and (2) an additional six counties had a change point that preceded
Meganís Law (Burlington, Camden, Monmouth, Salem, Somerset, and Union). This
means that only nine counties have a change point after Meganís Law was passed
with the years of change falling between 1994 and 1998. One final observation of
county contrast should be noted. In several cases, counties had substantial
drops in sex offenses after Meganís Law was enacted. However, in the last
several years these counties have had substantial increases in sex offense rates
(analyses not shown). This is true, for example, of Ocean, Hudson, and Warren
Counties.

Table 1. County and State Summary
Statistics for Sex Offenses

County

Population in 1994

Average Rate

Highest (Year)

Lowest (Year)

Change Year

Atlantic

236,589

71.0

128 (1991)

31 (2005)

1994

Bergen

848,392

32.0

71 (1988)

24 (2002)

n.s.

Burlington

407,060

30.4

51 (1985)

16 (2002)

1993 **

Camden

508,479

42.9

97 (1986)

29 (2005)

1989 **

Cape May

99,561

72.2

111 (1992)

38 (2003)

1995

Cumberland

144,544

91.1

127 (1992)

63 (2001)

1998

Essex

784,460

67.6

95 (1990)

35 (2004)

1994

Gloucester

242,161

35.6

53 (1993)

22 (2005)

1997

Hudson

572,720

44.0

56 (1993)

33 (2001)

1998

Hunterdon

113,522

18.3

32 (1985)

9 (2004)

n.s.

Mercer

335,229

46.4

67 (1986)

35 (2005)

n.s.

Middlesex

701,090

27.1

38 (1985)

19 (2004)

1998

Monmouth

577,069

37.6

56 (1988)

25 (2002)

1992 **

Morris

439,533

23.1

33 (1986)

15 (1993)

n.s.

Ocean

461,152

24.7

38 (1993)

15 (2001)

1996

Passaic

478,164

50.8

82 (1997)

36 (1988)

n.s.

Salem

64,691

50.8

78 (1991)

27 (2005)

1992 **

Somerset

262,243

18.9

27 (1988)

10 (1998)

1991 **

Sussex

137,021

21.8

32 (1999)

12 (2005)

n.s.

Union

504,864

30.0

53 (1986)

13 (2004)

1993 **

Warren

95,762

36.4

63 (1987)

14 (2001)

1996

NEW JERSEY

39.8

51 (1986)

29 (2005)

1994

**Change
point precedes implementation point

Also, many counties demonstrated a predictable ďjumpĒ after Meganís Law was
implemented. After a large initial drop in rates, there was a large rebound in
sexual offenses (but not as high as pre-Meganís Law levels), followed by a
continued decline. One example of this phenomenon is Cumberland County. As can
be seen in Figure 2, the large dip at year 10 (1994) is followed by a spike the
following year and then returns to a downward trend. This spike in sexual
offenses most likely reflects increased surveillance and arrests, rather than
increased offending.

Although individual counties vary, the aggregate state statistics indicate a
significant change in trend in the year 1994 (MW-U=110.0, p<.001). Figure 3
displays the rates before and after the implementation of Meganís Law. The upper
line represents sex offenses for the years 1985-1994, and the lower line
represents sex offenses for the years 1995-2005. Superimposed on the yearly
rates is a linear trend line. There are two important differences between these
trend lines. First, beginning in 1995 the rate of sex offenses never again
approaches the pre-1994 levels (i.e., the intercept and average are different).
Second, the slope is steeper in the post-Meganís law period. This is
particularly notable, since sex offenses are low base rate crime. The fact that
the decrease accelerates as the number of crimes decreases is unexpected. In
fact, one might expect that an effective intervention would exhibit diminishing
returns over time. This is not the case in this instance.

The aggressiveness with
which arrest, prosecution and surveillance of specific crimes is pursued changes
over time. After Megan Kankaís death at the hands of a convicted sex offender,
public sentiment demanded an immediate and aggressive response by law
enforcement, the courts and corrections. However, sex offenses are not the only
crimes to receive this type of attention. The federal War on Drugs was
experienced at the state and local level as well. Special task forces and
interdiction programs resulted in vast numbers of arrests. At the same time, the
crack epidemic hooked thousands of individuals. It is difficult to disentangle
the effects of law enforcement and prosecution efforts from addiction trends. In
the case of sex offenses, the trend in reduced rates of offending preceded
Meganís Law. The challenge of this analysis is to separate the effects of
intervention from the existing rate reduction momentum. The first set of
analyses addressed this point. The second concern is to control for historical
effects. Drug offenses, like sex offenses, should reveal rate patterns
consistent with intervention efforts. Other crimes should be more resistant to
these specialized influences, but sensitive to larger social and political
influences. The following analyses contrast the statewide sex offense trends
with drug and other non-sex/non-drug offense trends.

Figure 4 displays the
rates of non-sex (non-drug) offenses. The average number of crimes per 1,000
population is 50.0 with the highest rate of offending at 56 in 1989 and the
lowest at 45 in 2003. As illustrated, there is a consistent increase in crime
rates in the late 1980ís, followed by a five- year decline. Over the next
several years the rates increased again, only to drop to their lowest levels in
recent decades.

For the last five years the rate has remained
stable at about 45 crimes per 1,000. In these data, there is a significant
change point in 1998 (MW-U=98.00; p=.005), indicating that the levels of crime
prior to 1998 were significantly higher than those after 1998.

Unlike general crime, drug-related crimes showed very different rates by year.
On average, there are 68 drug crimes per 10,000 population. This varied from a
high of 89 in 1989 to a low of 52 in 1985. As can be seen in Figure 5, drug
crimes spiked in 1989, then dropped precipitously. Although the rates increased
again following 1993, this never again approached the 1989 rate. The most recent
decline appears be to be stable at around 65 crimes per 10,000 and has not
achieved the 1985-86 rates. There is no significant change point.

The general decline in sex offenses in NJ is similar to that of non-sex/non-drug
crimes. However, the statewide change point for sex offenses occurred during the
Meganís Law implementation year (i.e., 1994), whereas the change in trend for
non-sex crimes occurred later, in 1998. The wide year-to-year fluctuations in
drug crimes in fact may reflect specific policy and practice efforts, although
those efforts were not sustained. In the case of sex offenses, the statewide
change occurred when it was predicted to change and has maintained its impact
over time.

For each of these cases, extensive demographic,
clinical, institutional and service use, criminal history, and crime offense
characteristics information was collected. This provides an opportunity to
contrast outcomes (i.e., recidivism, time to failure, and harm variables) of
offenders arrested and released prior to the passing of Meganís Law with
offenders arrested and released after the legislation passed.

The
following sections present offender characteristics, bivariate differences in
characteristics, and pre-post group outcomes.

Results

Demographic
Characteristics

Table 2 displays the demographic characteristics
of the sample. The sample is comprised only of males. Half of the sample is
white with black and Hispanic offenders accounting for 35% and 15%,
respectively. Only 0.2% of offenders classified themselves as ďOther.Ē At
release, offenders were 34 years of age (sd=12.2). Nearly half (49%) were
married at one time and 66 percent had at least one child (including
stepchildren). On average, each individual had 1.9 children (sd=2.1).

Table 2. Demographic Characteristics
of Sex Offenders (n=550)

Variable

%

Mean (sd)

Race

50.5

% white

% black

34.8

% hispanic

14.6

% other

0.2

Average Age

34.1 (12.2)

% Ever Married

49.0

% With Children

65.9

Average Number of
Children

1.9 (2.1)

Education
Level

% less than high
school

50.3

% high school
diploma/GED

33.6

% some college or
more

16.1

% Ever Employed

62.8

Employment
Type

% white
collar/professional

7.8

% blue
collar/skilled trade

75.4

% service
industry

13.2

% other

3.6

Half of the sample never completed high
school. Specifically, 14 percent only achieved an eighth grade education,
whereas 36 percent attended high school, but did not graduate. Twenty-five
percent completed high school and 8 percent obtained a GED. Sixteen percent had
some college education with 4 percent completing an Associate Degree or higher.
Sixty-three percent had an employment history of a year or greater prior to
committing the offense. Although most offenders reported some variety of
employment history, the median years of employment was considerably low, at less
than three years of past employment. Of those who had been employed, most had
held unskilled or trade jobs (75%) or jobs in the service industry (13%). A
notable 8 percent held white-collar or professional jobs. Offendersí prior
employment income was unable to be determined for 29% of the sample. Of those
offenders reporting employment income, 25% reported an income of $20,000 or
less, 5% reported an income of $21,000 to $30,000, 3% reported an income of
$31,000 to $40,000, 1% reported an income of $41,000 to $50,000, and 0.5%
reported an annual income of $50,000 or higher.

Most offenders were raised in either a traditional two-parent home (66%) or in a
mother-only headed household (23%), and the majority of offenders did not report
any history of child abuse (61%). Twenty-six percent, however, reported having
experienced sexual abuse as a child. A large majority of offenders (91%) did not
have any family members involved in the criminal justice system.

Only 23 percent of offenders reported some type of past mental health problem.
These mental health issues included problems diagnosed in childhood (e.g.,
emotionally disturbed, developmental disorder) as well as more common diagnoses
problems such as depression. In addition, a sizeable proportion of offenders had
a drug or alcohol abuse history, with 45% reporting a prior drug abuse problem
and 47% reporting a prior alcohol abuse problem.

Thirty-five percent reported having received mental health treatment in the
past. Most offenders (94%) were reported as receiving some type of sex offender
treatment while incarcerated. A majority of offenders (88%) also received
treatment in addition to the standard, mandated treatment groups. Types of
adjunct treatment offered to inmates included adult basic education classes,
life/social skills groups (e.g. anger management), and drug and alcohol
counseling.

Offender Criminal History

Offender
criminal history includes information on prior arrests. These data are presented
in Table 4.

In general, the men incarcerated for a sex crime were more likely to have been
engaged in previous non-sex crimes than in sex crimes per se. Sixty-five percent
had a previous arrest for a non-sex crime. On average, they had been arrested
3.4 times (sd=5.77) and were arrested for the first time when they were 21.5
years old (sd=8.21). Only 27 percent had been previously arrested for a violent
crime with an average of .5 prior arrests (sd=1.07). Even fewer (24%) had been
arrested for a sex crime in the past, with an average number of .4 prior arrests
(sd=1.02). On average, these offenders were 24.8 years old (sd=9.01) at the time
of their first arrest for a sex crime. Only 6 percent had been arrested as a
juvenile for a sex crime.

Table 4. Offender Criminal History

Variable

%

Mean (sd)

% with Any Prior Arrests

64.9

Average Number of Arrests

3.64 (5.77)

Average Age at First Arrest

21.5 (8.21)

% with Prior Arrests for a
Violent Crime

27.3

Average Number of Arrests for
Violent Crime

.50 (1.07)

% with Prior Arrests for a
Sex Crime

23.5

Average Number of Arrests for
a Sex Crime

.43 (1.02)

Average Age at First Arrest
for a Sex Crime

24.8 (9.01)

% with a Juvenile Arrest for
a Sex Crime

5.7

Target Offense Characteristics

Table 5 displays information regarding the sex crime(s) for which the men in the
sample were serving sentences. Eighty percent of offenders were serving time for
child molestation (incest=21% vs. non-incest=59%). Cases of rape and general
exhibitionism accounted for 20% and 0.4% of all cases, respectively.

Sixty-two percent of offenders denied committing certain acts of the instant
crime, or denied the sexual offense in its entirety. Most often, offenders in
this latter group denied the more egregious acts of the offense (i.e.
penetration) or instances of multiple acts. According to police reports,
however, a majority of offenders (55%) engaged in multiple acts over a period of
time, and in 26 percent of the cases the offender had multiple victims.

The 550 offenders in the sample victimized a total of 796 individuals. That is
an average of 1.45 victims (sd=1.07) per offender for the current offense alone.
However, this number is skewed. In 74 percent of the cases, there was only one
victim identified. Of the cases involving two or more victims, the average
number of victims was 2.7 (sd=1.49). Of the victims, 79 percent were female and
30 percent were male. These percentages include the cases where both males and
females were victims (8%). The mean age of victim in the index offense was 12.3
years old (sd = 9.74). Ages of victims spanned from 1 year to 87 years old; 65
percent of the victims were 12 or younger, 24 percent were between 13 years old
and 18, and the remaining 11 percent were 19 or older.

Table 5. Characteristics of Target
Crime

Variable

%

Mean (sd)

Offense Type

% child
molestation

79.5

% rape

20.2

%
exhibitionism/voyeurism

0.4

% Offender
Denied Some or All Aspects of Crime

62.2

% Cases
Occurring Over Multiple Dates

55.2

% Cases Involving Multiple
VictimsVictim Gender

26.0

% male

21.1

% female

70.5

% both

8.4

Mean Age of Victim

12.3 (9.74)

Age Group of Victims

1.4 (1.1)

% 12 and under

65.4

(11)

% 13 through 18

23.7

% 19 or older

10.9

Relationship of Offender to Victim

% stranger

16.1

% family

48.2

% acquaintance

33.6

% significant
other

2.2

% Lived With
Victim

42.6

% Crime Occurred
in Victim or Offender Home

77.2

% Cases
Involving Weapon Use

13.2

Type of Weapon

% gun

27.3

% knife

51.5

%
rope/tape/bondage

7.6

% other

13.6

% Drugs Involved
in Crime

13.4

% Alcohol
Involved in Crime

26.0

Most offenders had an established prior relationship with their victims, with
only 16 percent of cases where the perpetrator was a stranger. In fact, nearly
half (48%) of the perpetrators were family members, with the remaining crimes
committed by either acquaintances of victims (34%) or victimsí significant
others (2%). Further, 43 percent of offenders lived with their victim(s) and in
77 percent of the cases the offense(s) were committed in the victimís or
offenderís home (including shared residence).

In 13 percent of the cases a weapon was used. Of those cases, the most common
weapon used was a knife (52%), followed by a gun (27%), other weapon (14%) or
the use of some form of restraint (8%). In 13 percent of the cases drugs were
involved and alcohol was involved in 26 percent of the offenses.

Criminal Justice
Factors

On average, offenders were sentenced to nearly
nine years of incarceration (104 months, sd= 63.8), with the most frequently
imposed sentence being five years. The minimum and maximum imposed sentences for
the sample were one year and 36 years, respectively. In actuality, offenders
served approximately five years on average (56 months, sd=40.4), with time
served ranging from three months to 21.5 years. Only 32 percent of offenders
were paroled whereas 68 percent maxed out; leaving the prison with no
post-incarceration supervision requirements other than those imposed by Meganís
Law.

Table 6. Criminal Justice Factors

Variable

%

Mean (sd)

Mean Length of Sentence
(in months)

104.4 (63.8)

Mean Time Served (in
months)

56.2 (40.4)

% Paroled

32.4

Sample Equivalences

In studies that use random sampling it is assumed
that the samples will be equivalent in all relevant factors. This is, however,
an assumption, and statistical theory suggests that although rare, samples may
be found to differ. In this case, it is known that samples differ temporally.
The differences in cohorts may be reflected in institutional responses (e.g.,
changes in court procedures. In this case ďTruth in SentencingĒ legislation came
into effect during this period), social or community behavior (e.g., increases
or drops in specific drugs of choice or type of crime), or other historical
sociopolitical changes. Bivariate analyses were conducted to confirm offender
similarity in: demographics, risk factors, and prior criminality; all known to
be associated with the likelihood of recidivism.

No statistically significant differences were
found in demographic characteristics. Among the risk factors, only receipt of
other treatment services was significant (with the earlier cohort more likely to
have received services [95% vs. 83%; χ2 = 14.6, df=1, p<.001]). In terms of
criminal history, no variable was found to be significant except for the average
number of prior sex offenses (with the earlier cohort averaging a higher number
[.56, sd=1.16 vs. .32, sd=.87; F=7.21, df=1, 546, p=.007]). Among the target
offense variables, only alcohol use was significant (with the earlier cohort
more likely to have used alcohol during the commission of the crime [31% vs.
22%; χ2 = 6.09, df=1, p=.014]). Thus of the over fifty variables analyzed, only
three were significantly different between groups. Again appealing to
statistical theory, with multiple tests there is an increased likelihood of
detecting significant relationships. No correction was made in these analyses to
account for this threat. However, given the vast number of equivalencies, these
groups are assumed equal for purposes of the outcome analyses.

Offender Outcomes Pre and Post-implementation
of Meganís Law

Before
presenting pre-post contrasts that are controlled by time at risk, year-by-year
graphs demonstrate several important points that must be kept in mind when
interpreting the remainder of the analyses. The outcome measure of recidivism
was collected through June 15, 2007. The remaining measures were adjusted to
assure that all offenders had an equal time at risk, specifically 2,358 days or
approximately six and a half years.

Figure 6
presents the percent of offenders released in each year who generally recidivate
within the follow-up period (i.e., 6 1/2 years). In this case, this figure
presents the percent of persons who are re-arrested, the percent of the sample
re-convicted and the percent re-incarcerated. Clearly, these are three closely
linked outcome measures (e.g., conviction cannot occur in the absence of a
chargeable offense).

Overall, 46 percent of offenders were re-arrested
(9 percent were re-arrested for a sex crime), 41 percent were convicted, and 35
percent were re-incarcerated. Although the figure shows substantial movement up
and down over time, there are no significant differences by year (this is
largely a power problem). Further, excluding the year 1995, all measures of
recidivism are declining over time from highs in the 50 to 60 percent range in
the 1990 release cohort to the 25 to 40 percent range in the 2000 release
cohort. What is interesting about this figure, however, is the rates relative to
each other within year. In most years, a stable percentage of persons who are
arrested are convicted. In this sample, over the 11 years, 88 percent who are
arrested are convicted. Of those convicted, 86 percent are incarcerated as a
result. However, these rates vary from year to year. For example, of the 1993
release cohort 46 percent were re-arrested; of those, 96 percent were convicted;
and of those convicted 96 percent went back to prison. In comparison, of the
1995 release cohort, 56 percent were re-arrested and nearly all were convicted
(96%), but only 70 percent of those convicted were re-incarcerated. It is not
clear from these data whether the year-to-year differences are a result of
procedural and administrative changes or a reflection of a system response to
public pressure.

Recidivism

Table 7 presents the comparisons of the pre and
post-implementation groups on all outcome measures, including recidivism,
community tenure and harm (sexual re-offending). In the first ďrecidivismĒ
section, all measures (i.e., arrest, conviction and incarceration) are
significant. In all three variables, the post-implementation group has a lower
percentage of cases that have experienced the outcome. This is for general
recidivism. Forty-one percent of the post-implementation group was re-arrested
compared to 50 percent of the pre-implementation group (χ2= 3.94, 1 df, p=.047).
Similarly, 34 percent of the post-implementation group was convicted compared to
46 percent of the pre-implementation group (χ2= 8.59, 1 df, p=.003). And 29
percent of the post-implementation group was re-incarcerated compared to 40
percent of the pre-implementation group (χ2= 7.53, 1 df, p=.006).

Time to failure is an important outcome measure.
Situations may exist where equal percentages of experimental and comparison
groups demonstrate an outcome, in this case, re-arrest, but the average length
of time to the arrest differs. Even in the case where equal percentages of pre
and post-implementation subjects are re-arrested, more days in the community
without committing a crime[2]
reflects improved outcomes in community and personal harm, as well as cost
savings.

The
average time to an arrest for any type of crime was 753 days (sd=628) or about
two years, one month (see Table 6). There was no
significant difference by implementation cohort. The average time to an arrest
for a sex offense was 795 days (sd=690) or about two years, two months. There
was no significant difference by implementation cohort for this variable.

A
survival analysis was also conducted on these data to determine whether the rate
of failure by time at risk varies significantly by implementation cohort. Figure
7 displays the survival curves for the two groups. Cases that experienced an
arrest are designated by their inclusion in the continuous curve (i.e.,
continuous line), cases that were not arrested are censored and are represented
as pluses. The strength of this analysis is the inclusion of censored cases.
They are included with the time value computed as the time from release until
the last day of data collection (i.e., June 15, 2007).

The curves reflect several facts: (1) all cases
are censored if their time at risk exceeds 2358 days regardless of whether they
were arrested or not, (2) 60 percent of post-implementation cases compared to 50
percent of pre-implementation cases survive (i.e., have not been arrested)[3],
and therefore visually demonstrating the cohort difference in overall
re-offending, and (3) the curves, while diverging a small amount, are
proportionally similar across time at risk, thus reflecting no significant
difference in the failure rate (confirmed by statistical tests, including the
log-rank test).

Reduced Harm by
Deterring Sexual Re-offending

Re-arrests for sexual offenses do not significantly differ year to year (see
Figure 8).

Holding time at risk constant, 9 percent of the sample has been re-arrested for
a sex crime, representing about 19 percent of the arrest charges. This varies
from a high of 14 percent in 1991 and 1992 to a low of 6 percent in 1994, 1995,
and 2000.

Pre and post-implementation groups do not differ in the percent of persons
re-arrested for a sex crime (10% vs. 7.6%). Of the 484 cases represented in the
sexual re-offense type analysis, 60 percent were charged with child molestation
or incest, 16 percent with rape and 24 percent with another type of sex offense,
including voyeurism and exhibitionism. The pre and post-implementation groups
also did not differ significantly on sex offense type.

As a side note, the percentage of violent crimes, excluding sex crimes, was also
investigated. Overall, 28 percent of the sample was re-arrested for at least one
violent crime. Importantly, only 21 percent of persons released after Meganís
Law was implemented were re-arrested for a violent crime compared to 32 percent
of the pre-implementation cohort.

PHASE THREE: COST STUDY

Methodology

The final stage of this research grant proved to be the most challenging, as
delineating costs associated with community registration and notification were
difficult to disentangle from other state and county level spending. The
research team mailed a cost assessment questionnaire to the Meganís Law Units
housed within each of the 21 county prosecutorís office. Meganís Law Units are
responsible for the enforcement and administration of community notification and
registration statutes in New Jersey (i.e., Meganís Law). Examples of functions
performed by Meganís Law Unit personnel include risk assessment (i.e., tier
classification), door to door/community notifications, trainings (e.g., law
enforcement, day care center employees), prosecution/litigation, internet
registry maintenance, etc.

Prior to mailing the cost assessment questionnaires, the research team met with
Assistant Prosecutors in order to review questions contained in the survey and
to address any questions prosecutors may have had in completing the survey.
Survey questions were subsumed under two general categories: start up costs and
ongoing yearly implementation costs.

In
addition, a section concerning percentage of time allotted to job tasks (i.e.
itemized according to staff title) was included and was to be completed for all
staff working within each countyís Meganís Law unit. For example, if an
investigator was included under personnel, a percentage breakdown of time
allotted to specific job functions such as risk assessment, door to door
notifications, training, etc. was required.

Of the 21 counties that were surveyed, 15 surveys were completed and received by
the research unit, for a total response rate of 71.4 percent. Upon receipt,
researchers scanned survey responses for possible misreading/interpretation
issues related to specific survey items. For additional clarification,
researchers called county prosecutor offices to confirm questionable survey item
responses and made any changes accordingly. After survey responses were
finalized, an Excel database of cost assessment variables was created for
analysis.

Along with the cost assessment survey, prior New Jersey state budgets were
reviewed for costs associated with the incarceration, rehabilitation, and
tracking of sex offenders. Specifically, the budgets were searched for any
allocation to Meganís Law. Moreover, original grant documentation and archived
folders were also reviewed for costs not included or found in the other sources.
Sources were challenging to locate, as was the origin of much of the funding.
Results

The results that follow include statistics based on the 15 counties that
responded to the research unitís Meganís Law Cost Assessment Survey. For the 15
responding counties, the initial aggregate implementation cost of Meganís Law
totaled $555,565. Of this total startup cost, establishment of the internet sex
offender registry accounted for $186,190, an average of $31,032 (sd=$24,140) per
county, equipment accounted for $232,407 ($19,367 average per county, sd=$14,212),
and other/miscellaneous costs accounted for $136,968 ($12,452 average per
county, sd= $17,702). In addition, total aggregate expenses for all 15 counties
attributable to the ongoing implementation of Meganís Law were estimated to be
$3,973,932 per annum (i.e., according to the fifteen participating counties). Of
total per annum costs, staffing costs accounts for $3,605,972 ($257,569 average
per county, sd= $160,180), internet sex offender registry maintenance accounts
for $146,300 ($20,900 average per county, sd=$20,178), equipment/supplies
accounts for $130,483 ($10,037 average per county, sd= $8,196), and
other/miscellaneous expenses accounts for $91,177 ($6,513 average per county, sd=
$6,002).

Additional information gathered from the prosecutorís surveys includes counts of
staff within each countyís Meganís Law Unit, number of cases handled per year,
and number of door to door notifications per year. According to completed
surveys, the number of employees dedicated to Meganís Law Unit operations totals
78 (5.2 average per county, sd= 3.2), and an estimated 5,873 Meganís Law
specific cases were processed (391.5 average per county, sd= 303.4). Moreover,
counties reported that law enforcement officers performed a total of 31
door-to-door notification events (3.9 average per county, sd= 2.7) throughout
the year (e.g. 1 event equals 300 households) for tier three sex offenders.

A question concerning
ongoing costs for the calendar year ending 2006 was also included in the survey
to measure yearly cost increases/decreases. The cost for Meganís Law
implementation during calendar year 2006 was estimated to be $1,557,978, whereas
implementation costs during calendar year 2007 totaled $3,973,932 for responding
counties[4].
This change represents a 155% increase in ongoing expenses from calendar year
2006 to calendar year 2007.

These increases were obtained from raw figures provided by the Meganís Law Units
and did not reflect specific costs. However, with the inception of the Global
Positioning Satellites used for Tier 3 sex offenders, it can be surmised that a
portion of the increases can be attributed to increased surveillance. Finally,
research of prior state budgets documented a $200,000 expenditure on Meganís Law
DNA Testing for fiscal years since 2000. There are no other distinguishable
appropriations. Most costs are combined with salaries or another type of
operating expenses.

PROJECT SUMMARY

The three phases of this
study were designed to test the effectiveness and cost of Meganís Law using
multiple methods and strategies. In none of the analyses was Meganís Law
definitively found to be effective. Since sex crime rates have been down prior
to Meganís Law and pre and post samples do not indicate statistically lower
rates of sexual offending, the high costs associated with Meganís Law are called
into question.

Summary of Results

As a preliminary step in assessing the effect of community registration and
notification laws on sexual arrest rates in New Jersey, the goal of the trend
study was to explore crime trends and to identify possible changes over a
21-year period. Specifically, the main research areas concerned the patterns of
sexual offense rates both prior and subsequent to the implementation of Meganís
Law, as well as comparisons in crime rates between sexual, drug, and
non-sex/non-drug based offenses during the same time period. The results
presented in this report support findings by other researchers exploring
relevant topics. Most notably, Finkelhor and Jones (2004) found that there has
been a consistent downward trend in child sexual abuses cases since the early
1990s.

This trend analysis did indeed find a significant change in the statewide
decreasing sex offense rate in the year Meganís Law was implemented, which may
lead some readers to believe that the legislation is solely responsible for the
decline. Because sex offense rates began to decline well before the passage of
Meganís Law, the legislation itself cannot be the cause of the drop in general.
It may, in fact, be the case that continuing reductions in sex offending in New
Jersey, as well as across the nation, are a reflection of greater societal
changes. Having said this, it is nevertheless hard to explain the steeper
decline in rates after the implementation of Meganís Law. Given that sex
offenses are low base rate events, the finding that these rates continue to
decline at an accelerated rate after 1994 suggests that something other than a
natural decline may be responsible. Although the initial decline cannot be
attributed to Meganís Law, the continued decline may, in fact, be related in
some way to registration and notification activities. However, there may well be
additional factors causing this steeper rate of decline after 1994, perhaps some
attributable to other public policies. For example, in 1998, New Jersey began
civilly committing those sex offenders found to present the highest risk to the
community, termed sexually violent predators. Assuming the accuracy of the risk
assessment that underlies the civil commitment of these sexually violent
predators, then those at highest risk to reoffend have been removed from the
community, thereby potentially lowering the sex offense rate, although, the
number of civilly committed sexual predators only includes approximately 350 sex
offenders.

Moreover, this statewide finding of a declining sex offense rate should be taken
with considerable caution. The variation in the pre-post-implementation rate
trends at the county level suggests that the statewide effect may be an artifact
of the aggregation process. Although many counties (9 of 21) follow the state
trend, many others show no differences in rates over time or have experienced
reductions followed by increases to near pre-Meganís Law levels.

Even so, with only two exceptions, the rates of sex offending were highest prior
to 1994 and lowest after 1995, with the most recent years having the lowest
rates. Differences in population, socio-political status, policing and
prosecutorial resources may be related to differences in the effectiveness in
notification and surveillance activities in specific counties.

Although impossible to distinguish the nature of the effects, the reductions of
sex offenses is related to some historical process: either (1)
registry/notification, surveillance and/or aggressive prosecution under a more
mature Meganís Law is responsible for the continued reductions or (2) general
public awareness, publicity, and/or exclusion and intolerance feed the continued
decline. Most likely, it is a combination of these factors.

In the offender release sample, there is a consistent downward trend in
re-arrests, reconvictions and re-incarcerations over time similar to that
observed in the trend study, except in 1995, when all measures spiked to a high
for that period. This resulted in significant differences between cohorts (i.e.,
those released prior to and after Meganís Law was implemented). Similarly,
re-arrests for violent crime (whether sexual or not) also declined steadily over
the same period resulting in a significant difference between cohorts (i.e.,
those released prior to and after Meganís Law was implemented). However, because
these trends began before Meganís Law was passed, this decline cannot be
attributed solely to Meganís Law activities.

In all other pre-post measures, including other measures of recidivism,
community tenure and harm reduction (decreased sexual offending), no significant
differences between cohorts were found. As such, Meganís Law does not illustrate
effectiveness in:

increasing community tenure (the time spent in the community prior to
re-arrest);

reducing sexual re-offenses;

changing the type of sexual re-offense or first time sexual offense (for
example, from hands-on to hands-off offenses); or

reducing the number of victims involved in sexual offenses.

Costs associated with the initial implementation of Meganís Law, as well as
ongoing expenditures, continue to grow over time. Start up costs totaled
$555,565 in 1994 and now current costs (in 2007) total approximately 3.9 million
dollars. Given the lack of demonstrated effect of Meganís Law, the researchers
are hard-pressed to determine that the escalating costs are justifiable.

Limitations

Conducting a study of this type with sensitive sexual arrest data introduces a
number of limitations. The most noted problem plaguing sexual offense research,
the low base rate of reported sexual offenses, is tied to the
under-representation of official data. Because sexual offenses are
under-reported, most measures of recidivism under-represent the true offending
rates (American Psychiatric Association [APA], 1999; Belknap, 2000; Furby et
al., 1989; Hall, 1995; Hanson & Bussiere, 1998). It has been suggested that the
present statistics on sexual abuse represent approximately one-third of the
number of actual victimizations, leaving researchers and practitioners concerned
about the ďdark figureĒ of sexual abuse (APA, 1999; Belknap, 2000; Chesney-
Lind, 1997). Legal definitions, fear and shame, and a desire for privacy are the
main contributors to the unwillingness of many victims to report their abuse.
Conversely, it has been noted that some types of sexual abuse may be
over-represented to the police, such as stranger rapes (Belknap, 2000).

For example, victims of stranger rape, as opposed to incest victims, may be more
inclined to report their sexual victimization because their perpetrator is
unknown. This disparity may lead many to believe that stranger victimizations
occur more frequently than other types of sexual victimizations because the
reports may appear disproportionately higher (Zgoba & Simon, 2004). Although
most individuals know that acquaintance or familial crimes are more frequent,
these factors may make it difficult to achieve a clear picture of sexual offense
rates (Belknap, 2000; Chesney- Lind, 1997). Given this low base rate of
reporting, it is notable that sex offenses decrease rapidly in the post-Meganís
law period; the fact that the decrease accelerates as the number of crimes
decreases is unexpected.

Another issue that has been difficult to fully address in the format of this
study is whether the noted decreases in the post-Meganís law period can be
attributed to specific deterrence or a more general deterrent effect. The intent
of Meganís law was to reduce repeat arrests among known sex offenders. That is,
Meganís law was designed as a specific deterrent. However, the idea of
notification and increased surveillance may have a general deterrent effect.
Further, increased attention and public contempt of sex offenses and offenders
may also contribute to general deterrence. This study illustrated downward
trends in sexual arrest rates, but cannot differentiate whether the reduction is
due to decreases in new first-time sex offenses (general deterrence) or to
decreases in sexual re-offenses (specific deterrence).

One of the largest challenges, and a subsequent limitation, associated with this
grant was obtaining the financial costs regarding Meganís Law. County Prosecutor
Offices, as well as the offices dealing with Treasury and Budget, had the same
difficulties the researchers experienced when attempting to isolate and identify
the costs listed in the State of New Jersey Budgets. Furthermore, initial
start-up costs were sometimes funded through grants that providing few specifics
regarding disbursement patterns. In an effort to provide close estimates, the
researchers developed proxy measures that should be read with some caution.

Conclusion

Despite wide community support for these laws, there is little evidence to date,
including this study, to support a claim that Meganís Law is effective in
reducing either new first-time sex offenses or sexual re-offenses. Continuing
research should focus on matching samples of sex offenders before and after the
implementation of Meganís Law and also examining levels of supervision
associated with Meganís Law. Further research will be conducted utilizing the
data accumulated here, specifically exploring low base rate offending and
potential predictors of sexual recidivism. Should future studies establish that
Meganís Law has no demonstrable effect on the rates of sexual offending, policy
makers and legislative leaders should investigate other options for lowering sex
offense rates, such as mandated treatment of all sex offenders, potential use of
polygraph testing and intensive probation and parole supervision.

[1]
No formal statistical tests were performed contrasting drug and
non-sexual offense rates to sex offense rates. The visual displays are
used to provide general contrasts, only.

[2]
Assuming that supervision and surveillance practices are equivalent and
that the individual does not indeed commit any crimes.

[3]
These are the same percentages in reverse (100%-%arrested) as those
displayed in Table 1

[4]
As noted, fifteen out of a possible twenty one counties in New Jersey
responded to the cost assessment survey, which translates to an
approximate response rate of 71.4%. In order to provide a more accurate
assessment of initial and on going costs statewide, said costs were
interpolated by adding 28.6% (i.e. 100% - 71.4%) to the implementation
and ongoing grand totals of the fifteen responding counties. . In
effect, using this general interpolation method, implementation costs
were estimated to be $714,457 and ongoing costs were estimated to be
$5,110,477 statewide. Again, because these figures are interpolated,
these costs do not take varying county demographics into account and
should be interpreted with this caveat.

ABOLISH SCARLET LETTER
PUNISHMENTTake Down The National
Sex-Offender Registry Ė It is a counter-productive law and violates 8th
& 14th Amendment Constitutional rights. ĖSIGN THE PETITIONor YOU may be next!

REPEAL JUDICIAL AND PROSECUTORIAL
IMMUNITYTerminate the archaic
English Feudalist Law that protects CPS workers, Police, Prosecutors
and Judges
from criminal prosecution and civil lawsuits when they violate a
citizen's Constitutional Rights.
Provide for compensatory and punitive damages to innocent people who
are railroaded by the Legal System.
Read the LEAD ARTICLE and follow links
to related information.
SIGN THE PETITIONbefore they get around to PERsecuting
YOU!

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